版本記錄
| 版本號 | 時間 |
|---|---|
| V1.0 | 2018.01.31 |
前言
人臉識別是圖像識別技術中的一種，廣泛的應用于很多領域，接下來這幾篇我們就一起來研究幾種關于人臉識別的技術。感興趣的可以參考上面幾篇文章。
1. 人臉識別技術 （一） —— 基于CoreImage實現(xiàn)對靜止圖片中人臉的識別
基于CoreImage的視頻中人臉識別技術
第一篇文章我們利用CoreImage對靜止的圖像進行人臉識別，相對來說，靜止圖像還是好識別的，如果要識別由攝像頭采集來的視頻中的人臉，那就相對來說難了，因為會有很多的性能問題。下面我們就一起看一下，利用AVFoundation進行圖像采集，利用CoreImage識別視頻中的人臉。
功能實現(xiàn)
還是直接看一下代碼。
#import "ViewController.h"
#import <AVFoundation/AVFoundation.h>
@interface ViewController () <AVCaptureVideoDataOutputSampleBufferDelegate>
@property (nonatomic, strong) AVCaptureSession *captureSession;
@property (nonatomic, strong) AVCaptureDevice *captureDevice;
@property (nonatomic, strong) AVCaptureDeviceInput *captureVideoDeviceInput;
@property (nonatomic, strong) AVCaptureVideoDataOutput *captureMovieFileOutput;
@property (nonatomic, strong) AVCaptureConnection *captureConnection;
@property (nonatomic, strong) AVCaptureVideoPreviewLayer *previewLayer;
@property (nonatomic, strong) NSMutableArray <UIView *> *faceViewArrM;
@end
@implementation ViewController
- (void)viewDidLoad
{
[super viewDidLoad];
self.faceViewArrM = [NSMutableArray array];
self.captureSession = [[AVCaptureSession alloc] init];
if ([self.captureSession canSetSessionPreset:AVCaptureSessionPresetHigh]) {
self.captureSession.sessionPreset = AVCaptureSessionPresetHigh;
}
else {
self.captureSession.sessionPreset = AVCaptureSessionPreset1280x720;
}
for (AVCaptureDevice *device in [AVCaptureDevice devices]) {
if ([device hasMediaType:AVMediaTypeVideo]) {
if (device.position == AVCaptureDevicePositionFront) {
self.captureDevice = device;
}
}
}
//添加輸入
[self addVideoInput];
//添加輸出
[self addVideoOutput];
//添加預覽圖層
[self addPreviewLayer];
[self.captureSession commitConfiguration];
[self.captureSession startRunning];
}
#pragma mark - Object Private Function
- (void)addVideoInput
{
NSError *error;
self.captureVideoDeviceInput = [AVCaptureDeviceInput deviceInputWithDevice:self.captureDevice error:&error];
if (error) {
return;
}
if ([self.captureSession canAddInput:self.captureVideoDeviceInput]) {
[self.captureSession addInput:self.captureVideoDeviceInput];
}
}
- (void)addVideoOutput
{
self.captureMovieFileOutput = [[AVCaptureVideoDataOutput alloc] init];
[self.captureMovieFileOutput setSampleBufferDelegate:self queue:dispatch_get_global_queue(DISPATCH_QUEUE_PRIORITY_HIGH, 0)];
self.captureMovieFileOutput.videoSettings = [NSDictionary dictionaryWithObjectsAndKeys:[NSNumber numberWithUnsignedInt:kCVPixelFormatType_32BGRA], (id)kCVPixelBufferPixelFormatTypeKey, nil];
if ([self.captureSession canAddOutput:self.captureMovieFileOutput]) {
[self.captureSession addOutput:self.captureMovieFileOutput];
}
//設置鏈接管理對象
self.captureConnection = [self.captureMovieFileOutput connectionWithMediaType:AVMediaTypeVideo];
//視頻旋轉方向設置
self.captureConnection.videoScaleAndCropFactor = self.captureConnection.videoMaxScaleAndCropFactor;;
//視頻穩(wěn)定設置
if ([self.captureConnection isVideoStabilizationSupported]) {
self.captureConnection.preferredVideoStabilizationMode = AVCaptureVideoStabilizationModeAuto;
}
// AVCaptureFileOutputDelegate *del = nil;
}
- (void)addPreviewLayer
{
self.previewLayer = [AVCaptureVideoPreviewLayer layerWithSession:self.captureSession];
[self.previewLayer setVideoGravity:AVLayerVideoGravityResizeAspect];
self.previewLayer.frame = self.view.bounds;
[self.view.layer addSublayer:self.previewLayer];
}
- (void)detectFaceWithImage:(UIImage *)image
{
// 圖像識別能力：可以在CIDetectorAccuracyHigh(較強的處理能力)與CIDetectorAccuracyLow(較弱的處理能力)中選擇，因為想讓準確度高一些在這里選擇CIDetectorAccuracyHigh
NSDictionary *opts = [NSDictionary dictionaryWithObject:
CIDetectorAccuracyHigh forKey:CIDetectorAccuracy];
// 將圖像轉換為CIImage
CIImage *faceImage = [CIImage imageWithCGImage:image.CGImage];
CIDetector *faceDetector = [CIDetector detectorOfType:CIDetectorTypeFace context:nil options:opts];
// 識別出人臉數(shù)組
NSArray *features = [faceDetector featuresInImage:faceImage];
// 得到圖片的尺寸
CGSize inputImageSize = [faceImage extent].size;
//將image沿y軸對稱
CGAffineTransform transform = CGAffineTransformScale(CGAffineTransformIdentity, 1, -1);
//將圖片上移
transform = CGAffineTransformTranslate(transform, 0, -inputImageSize.height);
//清空數(shù)組
dispatch_async(dispatch_get_main_queue(), ^{
[self.faceViewArrM enumerateObjectsUsingBlock:^(UIView * _Nonnull obj, NSUInteger idx, BOOL * _Nonnull stop) {
[obj removeFromSuperview];
obj = nil;
}];
});
// 取出所有人臉
for (CIFaceFeature *faceFeature in features){
//獲取人臉的frame
CGRect faceViewBounds = CGRectApplyAffineTransform(faceFeature.bounds, transform);
CGSize viewSize = self.previewLayer.bounds.size;
CGFloat scale = MIN(viewSize.width / inputImageSize.width,
viewSize.height / inputImageSize.height);
CGFloat offsetX = (viewSize.width - inputImageSize.width * scale) / 2;
CGFloat offsetY = (viewSize.height - inputImageSize.height * scale) / 2;
// 縮放
CGAffineTransform scaleTransform = CGAffineTransformMakeScale(scale, scale);
// 修正
faceViewBounds = CGRectApplyAffineTransform(faceViewBounds,scaleTransform);
faceViewBounds.origin.x += offsetX;
faceViewBounds.origin.y += offsetY;
//描繪人臉區(qū)域
dispatch_async(dispatch_get_main_queue(), ^{
UIView* faceView = [[UIView alloc] initWithFrame:faceViewBounds];
faceView.layer.borderWidth = 2;
faceView.layer.borderColor = [[UIColor redColor] CGColor];
[self.view addSubview:faceView];
[self.faceViewArrM addObject:faceView];
});
// 判斷是否有左眼位置
if(faceFeature.hasLeftEyePosition){
NSLog(@"檢測到左眼");
}
// 判斷是否有右眼位置
if(faceFeature.hasRightEyePosition){
NSLog(@"檢測到右眼");
}
// 判斷是否有嘴位置
if(faceFeature.hasMouthPosition){
NSLog(@"檢測到嘴部");
}
}
}
#pragma mark - AVCaptureVideoDataOutputSampleBufferDelegate
- (void)captureOutput:(AVCaptureFileOutput *)output didOutputSampleBuffer:(CMSampleBufferRef)sampleBuffer fromConnection:(AVCaptureConnection *)connection
{
NSLog(@"----------");
[connection setVideoOrientation:AVCaptureVideoOrientationPortrait];
CVImageBufferRef buffer;
buffer = CMSampleBufferGetImageBuffer(sampleBuffer);
CVPixelBufferLockBaseAddress(buffer, 0);
uint8_t *base;
size_t width, height, bytesPerRow;
base = (uint8_t *)CVPixelBufferGetBaseAddress(buffer);
width = CVPixelBufferGetWidth(buffer);
height = CVPixelBufferGetHeight(buffer);
bytesPerRow = CVPixelBufferGetBytesPerRow(buffer);
CGColorSpaceRef colorSpace;
CGContextRef cgContext;
colorSpace = CGColorSpaceCreateDeviceRGB();
cgContext = CGBitmapContextCreate(base, width, height, 8, bytesPerRow, colorSpace, kCGBitmapByteOrder32Little | kCGImageAlphaPremultipliedFirst);
CGColorSpaceRelease(colorSpace);
CGImageRef cgImage;
UIImage *image;
cgImage = CGBitmapContextCreateImage(cgContext);
image = [UIImage imageWithCGImage:cgImage];
[self detectFaceWithImage:image];
CGImageRelease(cgImage);
CGContextRelease(cgContext);
CVPixelBufferUnlockBaseAddress(buffer, 0);
}
@end
下面看一下部分輸出
2018-01-31 14:18:07.001789+0800 JJFaceDetector_demo2[4700:1444754] ----------
2018-01-31 14:18:07.168074+0800 JJFaceDetector_demo2[4700:1444754] 檢測到左眼
2018-01-31 14:18:07.168400+0800 JJFaceDetector_demo2[4700:1444754] 檢測到右眼
2018-01-31 14:18:07.168557+0800 JJFaceDetector_demo2[4700:1444754] 檢測到嘴部
2018-01-31 14:18:07.174485+0800 JJFaceDetector_demo2[4700:1444754] ----------
2018-01-31 14:18:07.388472+0800 JJFaceDetector_demo2[4700:1444754] 檢測到左眼
2018-01-31 14:18:07.389386+0800 JJFaceDetector_demo2[4700:1444754] 檢測到右眼
2018-01-31 14:18:07.389440+0800 JJFaceDetector_demo2[4700:1444754] 檢測到嘴部
2018-01-31 14:18:07.398383+0800 JJFaceDetector_demo2[4700:1444754] ----------
2018-01-31 14:18:07.587945+0800 JJFaceDetector_demo2[4700:1444754] 檢測到左眼
2018-01-31 14:18:07.588429+0800 JJFaceDetector_demo2[4700:1444754] 檢測到右眼
2018-01-31 14:18:07.588796+0800 JJFaceDetector_demo2[4700:1444754] 檢測到嘴部
... ...
下面看一下識別的效果
這個是我自己，不露臉了怕嚇到諸位，不過還是可以識別的
另外一個手機中的范爺圖片
移動另外一個手機中的范爺圖片
幾個需要說明的問題
1. info.plist文件添加key
這個簡單的說一下就可以了，iOS 10以后，相機權限需要增加key了。
2. 性能問題
移動的時候如果移動過快會有檢測不準確的現(xiàn)象，這個是由于，識別和計算臉部位置并進行標記，但是計算好如果正好進行了移動，那么標記的可能還是上一幀的位置，所有有時候標記不那么準確。
3. 部分代碼說明
先說一下這一句代碼，假如不添加下面這句代碼
self.captureMovieFileOutput.videoSettings = [NSDictionary dictionaryWithObjectsAndKeys:[NSNumber numberWithUnsignedInt:kCVPixelFormatType_32BGRA], (id)kCVPixelBufferPixelFormatTypeKey, nil];
我們運行下，看輸出
2018-01-31 14:32:57.312082+0800 JJFaceDetector_demo2[4706:1448810] ----------
2018-01-31 14:32:57.312320+0800 JJFaceDetector_demo2[4706:1448810] [Unknown process name] CGBitmapContextCreate: invalid data bytes/row: should be at least 2880 for 8 integer bits/component, 3 components, kCGImageAlphaPremultipliedFirst.
2018-01-31 14:32:57.312431+0800 JJFaceDetector_demo2[4706:1448810] [Unknown process name] CGBitmapContextCreateImage: invalid context 0x0. If you want to see the backtrace, please set CG_CONTEXT_SHOW_BACKTRACE environmental variable.
2018-01-31 14:32:57.312468+0800 JJFaceDetector_demo2[4706:1448810] [api] -[CIImage initWithCGImage:options:] failed because the CGImage is nil.
這里提示的意思是CGBitmapContextCreate創(chuàng)建上下文和圖像失敗了，是一個無效的數(shù)據(jù)位，我在stackOverFlow中找到了答案，有人和我碰到了一樣的問題。
看一下別人的Answers
Your best bet will be to set the capture video data output's
videoSettingsto a dictionary that specifies the pixel format you want, which you'll need to set to some variation on RGB that CGBitmapContext can handle.
The documentation has a list of all of the pixel formats that Core Video can process. Only a tiny subset of those are supported by CGBitmapContext. The format that the code you found on the internet is expecting iskCVPixelFormatType_32BGRA, but that might have been written for Macs—on iOS devices,kCVPixelFormatType_32ARGB(big-endian) might be faster. Try them both, on the device, and compare frame rates.
下面我給大家翻譯下
您最好的選擇是將捕獲視頻數(shù)據(jù)輸出的
videoSettings設置為一個字典，該字典指定了您想要的像素格式，您需要在CGBitmapContext可以處理的RGB上設置一些變量。
文檔中列出了a list of all of the pixel formats that Core Video can process。CGBitmapContext僅支持其中的一小部分。 您在互聯(lián)網(wǎng)上找到的代碼的格式是kCVPixelFormatType_32BGRA，但可能已經(jīng)為iOS設備上的Mac編寫，kCVPixelFormatType_32ARGB（big-endian）可能會更快。 在設備上試用它們，并比較幀速率。
所以加上上面那個setting字典就解決了問題。
后記
本篇已結束，后面更精彩~~~
